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題名：模糊環境下導入新設備之評估模型研究
作者：陳富雄
作者(外文)：FU-HSIUNG CHEN
校院名稱：國立臺灣科技大學
系所名稱：管理研究所
指導教授：林孟彥
學位類別：博士
出版日期：2012
主題關鍵詞：多屬性決策；模糊理論；模糊簡單加權；群決策；創新設備；Multiple attribute making decision；Fuzzy theory
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近來科技發展快速，產品生命週期也越來越短。為期提升競爭力、客戶滿意度及獲利率，各行業者日趨重視投資案之評估與選擇。新的科技產品固然有助於提高生產力、客戶滿意度和獲利能力，惟對新設備的投資決策也須更加慎重。創新設備布置之選擇屬於問題決策，涉及公司營運成本與收益，關係到企業是否能夠在競爭激烈的環境下成長，僅考量成本之傳統決策方式無法涵蓋公司之品質策略。
　　本研究利用模糊多屬性決策理論的簡單加權概念，對不確定環境下之創新設備選擇，提出兼顧品質與成本的評價方法。這項研究模型除了考量成本投資，並結合企業品質策略目標，作出整體性評價，讓決策者能選出最佳投資方案。
本研究以導入都會小型光纖網路作個案分析，程序上分為三個階段：（1）設定可行性方案： 群決策前，先衡量可行的方案數。（2）篩選屬性與分配權重：決策者對於不同的屬性會有不同的偏好傾向，各屬性會配置不同權重並加以正規化處理。（3）選擇方案：依據不同傳輸距離，選出最佳方案。
本研究導出之決策過程，貼近實際情況，系統程序更直接、有效，可以延伸使用於其他的管理，如人才選拔，供應商的評價和選擇，…等管理問題。
Recently, the product life cycles are becoming shorter due to the rapid development of science and technology. In order to enhance the competitiveness, customer satisfaction and profitability, the enterprises always take a great effort to evaluate and select the optimal investment proposals. Although new technology products can be used to improve productivity, customer satisfaction and profitability, the decisions for introducing new equipments need to be more careful. Selection of new equipment is one of problem decision-making, involving the company's operating costs and benefits. It will affect the growth of the enterprise in a competitive environment. The traditional decision-making, rather than considering the cost, cannot satisfy the quality of strategy goal.
This study applies the concept of simple additive weighting under fuzzy environment, a method of multi-attribute decision-making. We propose a model to evaluate the new equipment proposal take a balance between quality and cost. The model studied considers the cost of investment, and also combines the corporate strategy objectives. The model makes the overall evaluation and support the decision-maker to choose the best investment project.
This study also proposes a case study, introducing a metropolitan fiber optic network. The judgmental decision-making process is divided into three stages: (1) Feasibility of the alternatives: to measure the number of feasible solutions. (2) Attribute selection and weight allocation: the decision makers have different preferences for different attributes, each attribute will be allocated with different weight and finally we normalize the weights. (3) Selection: According to different distance transmitted, we select the optimal solution.
This study proposes a decision-making process, which closer to the actual situation. The process used is more direct, effective, and can be extended to other problems such as personnel selection, supplier evaluation and other issues.
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